Fig 1.
The NCGA starts with representation of the solution by GA and CCA. Then the Newton method is applied in order to evaluate the solution.
Fig 2.
The representation of nonlinear equations system variables by sub-chromosomes.
Each variable in nonlinear equations system represented by sub-chromosome and evolve in their own sub-population.
Fig 3.
Cooperative chromosome representation.
A representative was selected from all sub-population in order to form the cooperative chromosome.
Fig 4.
The pseudocode of the Newton cooperative genetic algorithm.
Fig 5.
Anaerobic fermentation pathway in S. cerevisiae.
Table 1.
Summary of metabolites and enzymes in case study 1.
Fig 6.
Tryptophan biosynthesis in E. coli pathway.
Table 2.
Details of component concentrations in case study 2.
Table 3.
Summary of parameter settings in producing the best result.
Table 4.
Best solution obtained using the NCGA in case study 1.
Table 5.
Best solution obtained using the NCGA in case study 2.
Fig 7.
The comparison results of the NCGA representation concept in case study 1.
Fig 8.
The comparison results of the NCGA representation concept in case study 2.
Fig 9.
The result of two-fitness evaluation concept in case study 1.
Fig 10.
The result of two-fitness evaluation concept in case study 2.
Table 6.
The comparison of computation time.